What is a 4th degree polynomial model calculator for this set of data:
1994 2814
1996 3603
1998 5429
2000 3962
2001 4117
2004 3840
http://www.xuru.org/rt/pr.asp
you need fifth degree
a x^5 + b x^4 etc to go through all the six points but can use fourth all right and get a least square fit.
by the way I would call 1994 x = 0
1996 x = 2, 1998 x = 4 , 2000 x = 6, 2001 x = 7, 2004 x = 10
then add 1994 to t at the end.
To calculate a 4th degree polynomial model for the given data set, you can use a mathematical software or programming language that supports polynomial regression analysis. Here's how you can do it using Microsoft Excel or Google Sheets:
1. Start by entering the given data into two columns, with the years in one column and the corresponding values in the other.
2. Select the data points and open the charting tool. In Excel, go to the "Insert" tab and select "Scatter" or "Scatter with Straight Lines" chart. In Google Sheets, click on the "Insert" menu, go to "Chart," and select "Scatter."
3. After creating the chart, right-click on any data point on the chart and select "Add Trendline." In the trendline options, choose "Polynomial" as the type of trendline.
4. Adjust the degree of the polynomial to 4 and make sure the equation is displayed on the chart. In Excel, this can be done by checking the box that says "Display Equation on Chart" in the trendline options. In Google Sheets, look for the "Trendline" tab in the chart editor and adjust the degree to 4.
5. The equation displayed on the chart is the 4th degree polynomial model that fits the given data.
If you prefer to use programming languages, such as Python or R, you can use libraries like NumPy, SciPy, or the polynomial regression functions provided by these languages to fit a 4th degree polynomial model to the data.
Please note that using a 4th degree polynomial model might not always be the most appropriate choice, and the degree of the polynomial should be chosen based on the specific characteristics of the data and the problem you are trying to solve.